AI Research Engineer (Multi-Modal & Vision)

About the job

As a member of the AI model team, you will drive innovation in training and optimizing vision-language models with a focus on real-world deployment. Your work will span the full model development lifecycle - from data curation and training pipeline design to model evaluation and optimization - with the goal of building models that are both highly capable and practical to deploy at scale.

You will work across a wide spectrum of multimodal architectures integrating text and vision, applying state-of-the-art research to improve model quality, efficiency, and domain-specific performance. We expect you to bring a research-driven mindset combined with strong engineering discipline - someone who can identify the right technique for a given problem, implement it rigorously, and measure its impact clearly.

You will work closely with a small, high-caliber team where your contributions will have direct and meaningful impact. If you are passionate about pushing the boundaries of what multimodal AI can achieve in production environments, this is your opportunity.

Responsibilities

• Conduct end-to-end research and engineering on vision-language models, covering training, evaluation, and optimization across the full model development lifecycle.
• Design and implement post-training pipelines including supervised fine-tuning, knowledge distillation, and reinforcement learning from human feedback.
• Develop and maintain high-quality multimodal datasets, including data curation, filtering, and balancing for domain-specific tasks.
• Drive model efficiency and deployability, adapting models for resource-constrained environments using compression and optimization techniques.
• Design and implement evaluation frameworks and benchmarks to measure model performance, robustness, and reliability.